2Jan 18

Culture circulates online within algorithm-driven networks: Google, Twitter, Facebook, Spotify, etc. These are also automatic measurement systems. Two particularly valuable things they measure are attribution – the path you took to reach something – and conversion (in its crudest form, did you buy it? but we can also throw in engagement, sharing, and other such soft interactions).

I’m using “valuable” here in the sense of “this is data marketers want”, which is why I’m also using the hard, gross language of attribution and conversion. Emotionally there’s a temptation to try and disengage from this, treating cultural objects (especially art, music, etc) as separate from the networks which reveal and sustain, but also exploit and reduce them.

I feel strongly that I don’t want to do this. If that data is powerful, I want to reclaim and name it for myself. I’m not talking about having more power over the algorithms that affect us and more visibility of their outcomes. That kind of thing is vital political work but as a writer about culture I also feel I should be keeping sight of the human and personal dimension of attribution and conversion – or, to use better words, provenance and use.

A formal project like my album listening one (a new-to-me record every day for a year) brought these elements to the fore. It’s an exercise in fitting listening into a daily routine (and letting that listening subtly change it) – i.e. use. And since you need to find a new thing every day, you need both open-ness (how do I get new ideas) and triage (how do I filter them)? This is what I mean by provenance – where did this thing come from and how did it reach me?

These pragmatic questions – how did I find out about this? Why did I decide to listen to it? What use did I make of it? – feel important to me, as much part of the experience as “did I like it?”, at least if answered honestly. (Working out how to answer them honestly is a job in itself). I want my writing to reflect them more.

Why are they important questions? I don’t know. I instinctively think they are, but I’m vaguer on the details. I can make two stabs at an explanation.

Part of it’s about self-presentation. We live in an era which flatters our sense of uniqueness. We’re encouraged to display ourselves as self-created individuals, polished bundles of tastes and experiences, ourselves consumable. Maybe paying honest attention to provenance and use demystifies cultural success, in the way that acknowledging privilege and luck can demystify material success.

And part of it’s economic. Talking about how culture reaches you is a conversation about supply chains, and it’s always good to think about supply chains! At least if you want to work out who owes (and does) what to whom. Putting a name and circumstance to the links in the chain nearest you is a step towards rehumanising the “attention economy” and the networks it relies on.

Comments

I’ve been thinking about this a lot. I wrote a semi-related post and have some further thoughts about this post specifically that I’m still thinking about and might stick here at some point. This post is specifically about what I’ve been calling “shillwave” — Spotify-inflated pop music that seems not to exist (critically or even popularly in other metrics like airplay) outside of the streaming service.

That is very interesting and will (time permitting) spark another response post… the one thing I’d clarify though is that for me at least attention provenance isn’t specifically anti-algorithmic. In this post I wanted to stress the role of human transmission (because I was putting my EOY lists together and kept realising that the categories “Lex records”, “Maura records”, “Chuck Eddy records” are as important to me as genre names.

But I don’t think of those as ‘higher’ categories than random Spotify discoveries, just more transparent ones. Part of the pleasure of the exercise has also been an awareness of my relationship with the Spotify algorithms – the constant and pleasurable improvising and negotiation that takes place around them. I need to go into more detail about this but I fundamentally don’t recognise some of the more horrified/paranoid descriptions of Spotify-influenced taste that have been making the rounds.

‘an awareness of my relationship with the Spotify algorithms – the constant and pleasurable improvising and negotiation that takes place around them.’

My thoughts about all services that aim to deliver more of what you like via algorithms is that both those who love and those who fear them underestimate the amount of work the user has to put in to even begin to get anything back – that’s a lot of music you have to listen to or TV shows you have to watch to start to train the system to begin to respond with recommendations you like. And, in my experience, it only gets better to a certain point and doesn’t keep improving.

(I realise that I’m a somewhat unhelpful subject in that my tolerance for listening to the same song a bunch of times is very low).

I’d be very happy if Spotify could somehow brainwash me and make me happy with what it chucks at me. As it is, I’ve given up on Discover Weekly almost entirely. Release Radar is much better, largely because of it’s non-mystical algorithm task of alerting me to the fact that Ghostface Killah has done a guest spot on someone’s song and First Aid Kit have a new record out.

I have encountered loads of music I like via Spotify, just as I have enjoyed films Netflix has nudged me towards etc. But it certainly hasn’t replaced either steers from people I know or stuff I’ve read about. And, to go back to my original point, if you don’t keep adding stuff yourself, Spotify recommendations fall into a rut very quickly.

(I still don’t understand why they refuse to have a ‘please, never ever suggest (eg) a sodding Bob Marley track to me ever again’ option).

Yeah, my comments there were sparked by your post but didn’t really engage with the thrust of it, which seemed to be as much about networks of real people as networks of algorithms and such. (My “going further” would be not only to bring in Lex and Maura and Chuck but also dishwashing and temper tantrums in the background and that time I went on the Cyclotron ten times in row and things that have nothing to do with anything, particularly, except everything. But I’m not ready to go there.)

Re: algorithms, my sense of Spotify is increasingly reminding me of following Radio Disney in the mid-00’s — some obvious machinations, some non-obvious ones, and a lot of cumulative advantage and serendipity happening.

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